Hailstorm characterization with a synergistic active and passive, GEO and LEO observation strategy

Convection is a vital process which helps to redistribute energy in the Earth atmosphere and is often conducive to cloud formation connected to severe weather events worldwide. Hail production can occur in these severe events highly impacting infrastructures and properties. Italy and the Mediterranean Basin in general are witnessing an increasing trend in the number of occurrences of such events in the last decades, thus calling for an advancement in the observational capability and retrieval methodologies for the analysis of convective storm associated to hail production.This work focuses on the analysis of few case studies occurred in Italy in August and September 2024. The aim is to evaluate the complementarity and the effectiveness of active and passive, GEO and LEO satellite instruments and satellite-based retrieval algorithms in convection and hailstorm identification. Convective clouds are analysed through the convection products from the EUMATSAT Satellite Application Facility in support to nowcasting and very short range forecasting computed using Meteosat Rapid Scan Service (RSS) data. Further information about updrafts and overshooting tops is acquired from the EarthCARE Cloud Profiling Radar (i.e., reflectivity and vertical velocity of cloud particles). The Multi-sensor Approach for Satellite Hail Advection (MASHA), a new multi-instrument technique conceived for real-time tracking of hail-bearing clouds, completed the set of analysis tools. It combines the hail probabilities computed through the Global Precipitation Measuring PMW sensor constellation, with the high temporal rate acquisition of GEO infrared brightness temperatures (IR-BT) from the Meteosat RSS. Exploiting constantly updated relationships between spatio-temporal co-located IR-BTs and PWM hail probabilities, MASHA monitors the evolution of hail-bearing systems at high spatio-temporal resolution (i.e., 4-5 km and 5 min., respectively).